JuliaAI / JuliaAI/MLJLinearModels.jl
NewtonCG is too slow
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Nobody has claimed this yet.
performances
- Dominant language
- Julia
- Stars
- 86
- Forks
- 15
- PR merge metrics
- No merged PRs in 30d
Description
It shouldn't be; this may be due to issues with the Krylov Solver; consider rewriting your own NewtonCG using the cg from IterativeSolvers & starting with a simple backtracking; maybe later with Hager-Zhang.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating NewtonCG and the current Krylov Solver implementation, then compare the solver approach with IterativeSolvers' cg. The issue suggests starting with simple backtracking and possibly later using Hager-Zhang, but it does not name files, tests, benchmarks, or a completion criterion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100